Abstract_sampler< Model > Class Template Reference

#include <sample_sampler.h>

Inheritance diagram for Abstract_sampler< Model >:

Public Types
typedef Sampler_step< Model >::Type	Step
typedef Model	Model_type

Public Member Functions
	Abstract_sampler (const Model &initial_state, double initial_log_target)
	BOOST_CONCEPT_ASSERT ((BaseModel< Model >))
virtual void	run (int num_iterations)
	Runs the sampler. This function runs the sampler for the indicated number of iterations. At each iteration it chooses a sampler step using choose_step() and invokes it using its operator(). The best model is saved and returned. More...
Model &	current_state ()
const Model &	current_state () const
double	current_log_target () const
template<class Recorder >
void	add_recorder (Recorder r)
template<class Recorder >
void	add_recorder (Recorder *r)
template<class Callback >
void	add_record_callback (Callback cb)
template<class Recorder >
const Recorder &	get_recorder (size_t i) const
void	if_accept (const Callback &cb)
void	if_reject (const Callback &cb)
void	on_accept (const Callback &cb)
void	on_reject (const Callback &cb)

Protected Member Functions
virtual const Step &	choose_step () const =0
	Chooses a sampler step. Pure virtual method, should be overwritten. More...

Detailed Description

template<typename Model>
class Abstract_sampler< Model >

Template Parameters

Model

The model type. Must comply with BaseModel concept.

A generic sampler. Concrete classes must implement:

(1) choose_step() - returns a sampler step function to run. (2) get_recorder() - returns a recorder object for keeping track of accepted samples.

As far as the steps are concerned, they need only comply with the SamplerStep concept. Similarly, the recorder must comply with ModelRecorder concept.

Member Typedef Documentation

template<typename Model>

typedef Model Abstract_sampler< Model >::Model_type

template<typename Model>

typedef Sampler_step<Model>::Type Abstract_sampler< Model >::Step

Constructor & Destructor Documentation

template<typename Model>

Abstract_sampler< Model >::Abstract_sampler ( const Model &  initial_state, double  initial_log_target  )

inline

Parameters

initial_state	Initial model to start the sampler with.
initial_log_target	The log of the target distribution at intitial_state

Member Function Documentation

template<typename Model>

template<class Callback >

void Abstract_sampler< Model >::add_record_callback ( Callback  cb )

inline

template<typename Model>

template<class Recorder >

void Abstract_sampler< Model >::add_recorder ( Recorder  r )

inline

template<typename Model>

template<class Recorder >

void Abstract_sampler< Model >::add_recorder ( Recorder *  r )

inline

template<typename Model>

Abstract_sampler< Model >::BOOST_CONCEPT_ASSERT

(

(BaseModel< Model >)

)

template<typename Model>

virtual const Step& Abstract_sampler< Model >::choose_step ( ) const

protectedpure virtual

Chooses a sampler step. Pure virtual method, should be overwritten.

Implemented in Single_step_sampler< Model >, and Multi_step_sampler< Model >.

template<typename Model>

double Abstract_sampler< Model >::current_log_target ( ) const

inline

Return the value of the log-target distribution evaluated at the current state (cached value, no cost incurred)

template<typename Model>

Model& Abstract_sampler< Model >::current_state ( )

inline

Return the current state of the sampler.

template<typename Model>

const Model& Abstract_sampler< Model >::current_state ( ) const

inline

Return the current state of the sampler. (const version)

template<typename Model>

template<class Recorder >

const Recorder& Abstract_sampler< Model >::get_recorder ( size_t  i ) const

inline

template<typename Model>

void Abstract_sampler< Model >::if_accept ( const Callback &  cb )

inline

Add a callback to be called if the next/current step is accepted This callback will be cleared at the end of the sampling iteration.

template<typename Model>

void Abstract_sampler< Model >::if_reject ( const Callback &  cb )

inline

Add a callback to be called if the next/current step is rejected. This callback will be cleared at the end of the sampling iteration.

template<typename Model>

void Abstract_sampler< Model >::on_accept ( const Callback &  cb )

inline

Add a callback to be called every time a step is accepted. If you want a callback to be called only if the next step is accepted, use if_accept().

If this is called multiple times, the callbacks will be called in sequence in the order they were added.

At the moment there is no way to remove a callback after it has been added. This could be added in the future if there is interest.

template<typename Model>

void Abstract_sampler< Model >::on_reject ( const Callback &  cb )

inline

Add a callback to be called every time a step is rejected. If you want a callback to be called only if the next step is rejected, use if_reject()

If this is called multiple times, the callbacks will be called in sequence in the order they were added.

At the moment there is no way to remove a callback after it has been added. This could be added in the future if there is interest.

template<typename Model >

void Abstract_sampler< Model >::run ( int  num_iterations )

virtual

Runs the sampler. This function runs the sampler for the indicated number of iterations. At each iteration it chooses a sampler step using choose_step() and invokes it using its operator(). The best model is saved and returned.

Parameters

initial_state	The initial value of the model; e.g., the initial state of the Markov chain in MH.
num_iterations	The number of iterations the sampler will do.

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The documentation for this class was generated from the following file:

• /work/kobus/src/lib/sample_cpp/sample_sampler.h